基于萤火虫群优化的小波常模盲均衡算法

An orthogonal wavelet transform constant modulus blind equalization algorithm based on glowworm swarm optimization algorithm

提出基于萤火虫群优化的小波常模盲均衡算法(GSO-WT-CMA),利用萤火虫群优化(GSO)算法良好的全局搜索能力来优化均衡器的初始权向量,结合正交小波变换(WT)降低信号自相关性,有效改善了常数模盲均衡算法(CMA)容易陷入局部最小值、收敛速度慢、稳态误差大等问题.水声仿真结果表明,新算法具有收敛速度快,均方误差小,能获得全局最优解等优点.

An orthogonal wavelet transform （WT） constant modulus blind equalization algorithm（CMA） based on artifieial glowworm swarm optimization algorithm（GSO）is proposed. In the proposed algo- rithm,CMA is integrated with GSO and WT, the de-correlation ability of WT is used to reduce the signal autocorrelation,and the global search ability of GSO algorithm is used to optimize the equalizer weight vector. It can reduce the mean square error of CMA and the possibility of CMA local convergence and im- prove the convergence rate of CMA. The results from computer simulation show that the proposed algo- rithm outperforms the CMA and WT-CMA in improving the convergence rate and reducing the steady- state error and computational loads.